Apply ruff formatting to codebase (#207)

## Summary

- Apply ruff code formatting across entire Python codebase for
consistent style
- Update CI workflow configuration
- All 237 tests pass (236 passed, 1 skipped)

### **Linting vs. Formatting with Ruff**

We have migrated to **Ruff**, which replaces several older tools with a
single, faster engine.

* **Formatting (Replaces [Black](https://github.com/psf/black)):**
Standardizes the visual style of the code, such as indentation, line
lengths, and quoting.
    * **How to run:** `ruff format .`
* **Linting (Replaces [Flake8](https://github.com/PyCQA/flake8) and
[isort](https://github.com/PyCQA/isort)):** Analyzes code for logical
errors, unused imports, or non-standard practices.
* **How to run:** `ruff check .` (use `ruff check --fix .` to
automatically resolve simple issues)

### **Current Policy**

* **Formatting is Enforced:** The CI pipeline will fail if the code is
not formatted. Please run `ruff format .` before every commit.
* **Linting is Recommended:** While we aren't enforcing strict linting
yet (due to the high volume of existing errors in the codebase), we
strongly encourage you to run check your changes to ensure new edits are
as clean as possible. For example, run `ruff check
ochre/Models/StateSpaceModel.py` check for lints in the
StateSpaceModel.py file.


### **Setting up Ruff**

To ensure your environment is set up correctly to use the new tooling,
please follow these steps:

1.  **Update your branch**
Merge the latest `dev` branch into your current feature branch to get
the new configuration files.

2.  **Install `uv`** if you don't already have it.
    We use `uv` for fast Python package management.
    You can install it from pip with:
  	 ```bash
     pip install uv
	```

    * **macOS / Linux:**
        ```bash
curl -LsSf
[https://astral.sh/uv/install.sh](https://astral.sh/uv/install.sh) | sh
        ```
    * **Windows:**
        ```powershell
powershell -ExecutionPolicy ByPass -c "irm
[https://astral.sh/uv/install.ps1](https://astral.sh/uv/install.ps1) |
iex"
        ```

3.  **Sync Dependencies**
If you already have a `.venv` folder in your project directory, please
delete it first to ensure a clean install. Then run:
    ```bash
    uv sync
    ```

4.  **Run Formatting**
You can run Ruff directly using `uv` (recommended) or by activating your
environment.

    * **Option A (Recommended):** Run via `uv`
        ```bash
        uv run ruff format .
        ```

    * **Option B:** Activate environment first
        * **macOS / Linux:**
            ```bash
            source .venv/bin/activate
            ruff format .
            ```
        * **Windows:**
            ```powershell
            .venv\Scripts\activate
            ruff format .
            ```

```

Author: jmaguire1

.github/workflows/tests.yml

@@ -4,7 +4,8 @@ on:
   push:
     branches: [main, dev]
   pull_request:
-    branches: [main, dev]
+    # Run on all pull requests
+    types: [opened, synchronize, reopened]
 
 jobs:
   test:
@@ -61,9 +62,8 @@ jobs:
           pip install ruff
 
       - name: Run ruff linter
-        run: ruff check ochre/ --output-format=github
+        run: ruff check . --output-format=github
         continue-on-error: true
 
       - name: Run ruff formatter check
-        run: ruff format ochre/ --check --diff
-        continue-on-error: true
+        run: ruff format . --check --diff

.gitignore

@@ -14,3 +14,4 @@ docs/_build
 *.code-workspace
 
 ochre/defaults/Input Files/OCHRE*
+.history

bin/compare_energyplus.py

@@ -1,38 +1,39 @@
 import os
 
-from ochre import Analysis, CreateFigures, Dwelling
+from ochre import Analysis, CreateFigures
 
 # Script to compare OCHRE and E+ outputs for generic model. Assumes both models have been run in the same folder
 
 # File locations
-main_path = os.path.join('path', 'to', 'ochre_folder')
-eplus_file = os.path.join(main_path, 'results_timeseries.csv')
-simulation_name = 'ochre'  # name for OCHRE files
+main_path = os.path.join("path", "to", "ochre_folder")
+eplus_file = os.path.join(main_path, "results_timeseries.csv")
+simulation_name = "ochre"  # name for OCHRE files
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     # Load OCHRE files
-    ochre_exact, ochre_metrics, ochre = Analysis.load_ochre(main_path, simulation_name, load_main=False, 
-                                                            combine_schedule=True)
+    ochre_exact, ochre_metrics, ochre = Analysis.load_ochre(
+        main_path, simulation_name, load_main=False, combine_schedule=True
+    )
 
     # Load E+ files
     eplus = Analysis.load_eplus_file(eplus_file, year=ochre.index[0].year)
 
     # keep days from OCHRE simulation
-    eplus = eplus.loc[ochre.index[0]: ochre.index[-1]]
+    eplus = eplus.loc[ochre.index[0] : ochre.index[-1]]
     eplus_metrics = Analysis.calculate_metrics(eplus, metrics_verbosity=6)
 
     # Compare metrics and save to file
     compare_metrics = Analysis.create_comparison_metrics(ochre, eplus, ochre_metrics, eplus_metrics)
-    metrics_file = os.path.join(main_path, simulation_name + '_comparison.csv')
+    metrics_file = os.path.join(main_path, simulation_name + "_comparison.csv")
     compare_metrics.to_csv(metrics_file)
 
-    print(f'Comparison Metrics for {simulation_name}:')
+    print(f"Comparison Metrics for {simulation_name}:")
     print(compare_metrics)
 
     # show plots
     # data = {'OCHRE (exact)': ochre_exact, 'OCHRE': ochre, 'E+': eplus}
-    data = {'OCHRE': ochre, 'E+': eplus}
+    data = {"OCHRE": ochre, "E+": eplus}
     # CreateFigures.plot_external(data)
     CreateFigures.plot_envelope(data)
     # CreateFigures.plot_hvac(data)

bin/run_cosimulation.py

@@ -1,7 +1,6 @@
 import os
 import json
 import datetime as dt
-import shutil
 import sys
 import click
 import helics
@@ -53,9 +52,7 @@
 
 # Note: see documentation for where to download other weather files
 # https://ochre-nrel.readthedocs.io/en/latest/InputsAndArguments.html#weather-file
-default_weather_file = os.path.join(
-    default_input_path, "Weather", "USA_CO_Denver.Intl.AP.725650_TMY3.epw"
-)
+default_weather_file = os.path.join(default_input_path, "Weather", "USA_CO_Denver.Intl.AP.725650_TMY3.epw")
 
 # control parameters - keep net load within +/- 1 kW per house
 min_net_load = -1 * n
@@ -97,7 +94,7 @@ def step_to(time, fed, offset=0):
         if t_new >= t_requested:
             return
         time.sleep(0.01)
-        
+
 
 @click.group()
 def cli():
@@ -209,9 +206,7 @@ def aggregator():
         results.append(total_powers)
 
         # determine battery setpoints to maintain net load limits
-        nonbattery_power = (
-            total_powers["Total Electric Power (kW)"] - total_powers["Battery Electric Power (kW)"]
-        )
+        nonbattery_power = total_powers["Total Electric Power (kW)"] - total_powers["Battery Electric Power (kW)"]
         if nonbattery_power > max_net_load:
             battery_power = max_net_load - nonbattery_power
         elif nonbattery_power < min_net_load:

bin/run_dwelling.py

@@ -2,6 +2,7 @@
 import datetime as dt
 
 from ochre import Dwelling, CreateFigures
+
 # from ochre import Analysis
 from ochre.utils import default_input_path
 
@@ -12,27 +13,23 @@
     #
     # Timing parameters
     "start_time": dt.datetime(2018, 1, 1, 0, 0),  # year, month, day, hour, minute
-    "time_res": dt.timedelta(minutes=60),         # time resolution of the simulation
-    "duration": dt.timedelta(days=1),             # duration of the simulation
+    "time_res": dt.timedelta(minutes=60),  # time resolution of the simulation
+    "duration": dt.timedelta(days=1),  # duration of the simulation
     "initialization_time": dt.timedelta(days=1),  # used to create realistic starting temperature
     # "time_zone": None,                          # option to specify daylight savings, in development
     #
     # Input files
     "hpxml_file": os.path.join(default_input_path, "Input Files", "bldg0112631-up11.xml"),
-    "hpxml_schedule_file": os.path.join(
-        default_input_path, "Input Files", "bldg0112631_schedule.csv"
-    ),
-    "weather_file": os.path.join(
-        default_input_path, "Weather", "USA_CO_Denver.Intl.AP.725650_TMY3.epw"
-    ),
+    "hpxml_schedule_file": os.path.join(default_input_path, "Input Files", "bldg0112631_schedule.csv"),
+    "weather_file": os.path.join(default_input_path, "Weather", "USA_CO_Denver.Intl.AP.725650_TMY3.epw"),
     # note: weather_path can be used when Weather Station is specified in HPXML file
     # "weather_path": weather_path,
     #
     # Output parameters
     # "verbosity": 3,                       # verbosity of time series files (0-9)
     # "metrics_verbosity": 3,               # verbosity of metrics file (0-9)
     # "save_results": False,                # saves results to files. Defaults to True if verbosity > 0
-    "output_path": os.getcwd(),             # defaults to hpxml_file path
+    "output_path": os.getcwd(),  # defaults to hpxml_file path
     # "save_args_to_json": True,            # includes data from this dictionary in the json file
     # "output_to_parquet": True,            # saves time series files as parquet files (False saves as csv files)
     # "save_schedule_columns": [],          # list of time series inputs to save to schedule file

bin/run_equipment.py

@@ -11,7 +11,6 @@
     ElectricResistanceWaterHeater,
     AirConditioner,
     ScheduledLoad,
-    EventBasedLoad,
     EventDataLoad,
 )
 from ochre import CreateFigures
@@ -45,7 +44,7 @@ def run_equipment_from_house_model(end_use):
 
     # Extract equipment by its name or end use
     equipment = dwelling.get_equipment_by_end_use(end_use)
-    
+
     # Update simulation properties to save results
     equipment.main_simulator = True
     equipment.save_results = True
@@ -130,8 +129,7 @@ def run_battery_from_schedule():
     # Note: can also be done at each time step, see run_external_control.py
     # for examples
     schedule = np.random.randint(-5, 5, len(battery.sim_times))
-    battery.schedule = pd.DataFrame({"Battery Electric Power (kW)": schedule},
-                                    index=battery.sim_times)
+    battery.schedule = pd.DataFrame({"Battery Electric Power (kW)": schedule}, index=battery.sim_times)
     battery.reset_time()  # initializes the new schedule
 
     # Simulate equipment
@@ -264,20 +262,24 @@ def run_hvac():
 
     # create example HVAC schedule
     # TODO: add solar radiation to schedule (in H_LIV)
-    times = pd.date_range(timing["start_time"], timing["start_time"] + timing["duration"], freq=timing["time_res"],
-                          inclusive="left")
+    times = pd.date_range(
+        timing["start_time"], timing["start_time"] + timing["duration"], freq=timing["time_res"], inclusive="left"
+    )
     deadband = (2 + 1 * np.random.randn(len(times))).clip(min=1)
     ambient_temp = 27 - np.abs(times.hour.values - 14) / 2 + 0.5 * np.random.randn(len(times))
     internal_gains = 100 + 30 * np.random.randn(len(times))
-    schedule = pd.DataFrame({
-        "HVAC Cooling Setpoint (C)": 22,
-        "HVAC Cooling Deadband (C)": deadband,
-        "Ambient Dry Bulb (C)": ambient_temp,
-        "Ambient Humidity Ratio (-)": 0.001,
-        # "Ambient Pressure (kPa)": 101,
-        # "T_EXT": ambient_temp,
-        "Internal Gains (W)": internal_gains,
-    }, index=times)
+    schedule = pd.DataFrame(
+        {
+            "HVAC Cooling Setpoint (C)": 22,
+            "HVAC Cooling Deadband (C)": deadband,
+            "Ambient Dry Bulb (C)": ambient_temp,
+            "Ambient Humidity Ratio (-)": 0.001,
+            # "Ambient Pressure (kPa)": 101,
+            # "T_EXT": ambient_temp,
+            "Internal Gains (W)": internal_gains,
+        },
+        index=times,
+    )
 
     envelope_args = {
         "capacitances": {
@@ -319,8 +321,7 @@ def run_hvac():
 
     print()
     # print(df.head())
-    CreateFigures.plot_daily_profile(df, "HVAC Cooling Electric Power (kW)",
-                                     plot_max=False, plot_min=False)
+    CreateFigures.plot_daily_profile(df, "HVAC Cooling Electric Power (kW)", plot_max=False, plot_min=False)
     CreateFigures.plot_hvac({"": df})
     # CreateFigures.plot_envelope({"": df})
     CreateFigures.plt.show()

bin/run_fleet.py

@@ -64,6 +64,7 @@ def run_ev_fleet(n=4, n_parallel=2):
     df.plot()
     CreateFigures.plt.show()
 
+
 def setup_wh(i):
     start_time = dt.datetime(2018, 1, 1, 0, 0)  # year, month, day, hour, minute
     time_res = dt.timedelta(minutes=1)
@@ -102,6 +103,7 @@ def setup_wh(i):
     # Initialize equipment
     return ElectricResistanceWaterHeater(**equipment_args)
 
+
 def run_water_heater_fleet(n=5):
     # Initialize equipment
     fleet = [setup_wh(i + 1) for i in range(n)]
@@ -113,7 +115,7 @@ def run_water_heater_fleet(n=5):
         all_data[wh.name] = df
 
     cols_to_plot = [
-        "Water Heating Electric Power (kW)", 
+        "Water Heating Electric Power (kW)",
         "Hot Water Outlet Temperature (C)",
         "Hot Water Delivered (L/min)",
     ]
@@ -142,11 +144,9 @@ def setup_battery(i):
     # Note: can also be done at each time step, see run_external_control.py
     # for examples
     schedule = np.random.randint(-capacity, capacity, len(battery.sim_times))
-    battery.schedule = pd.DataFrame(
-        {"Battery Electric Power (kW)": schedule}, index=battery.sim_times
-    )
+    battery.schedule = pd.DataFrame({"Battery Electric Power (kW)": schedule}, index=battery.sim_times)
     battery.reset_time()  # initializes the new schedule
-    
+
     return battery
 
 
@@ -170,7 +170,7 @@ def run_battery_fleet(n=4):
     CreateFigures.plt.show()
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     run_ev_fleet()
     # run_water_heater_fleet()
     # run_battery_fleet()

bin/run_multiple.py

@@ -2,7 +2,7 @@
 import shutil
 
 from ochre import Analysis
-from ochre.cli import create_dwelling, limit_input_paths, run_multiple_local, run_multiple_hpc
+from ochre.cli import create_dwelling
 from ochre.utils import default_input_path
 
 # Examples to download and run multiple Dwellings. Uses OCHRE's command line
@@ -48,9 +48,7 @@ def compile_results(main_path, n_max=None):
     df.to_csv(os.path.join(output_path, "all_ochre_inputs.csv"))
 
     # combine metrics files
-    metrics_files = {
-        name: os.path.join(path, "ochre_metrics.csv") for name, path in run_names.items()
-    }
+    metrics_files = {name: os.path.join(path, "ochre_metrics.csv") for name, path in run_names.items()}
     df = Analysis.combine_metrics_files(metrics_files)
     df.to_csv(os.path.join(output_path, "all_ochre_metrics.csv"))
 

bin/run_panel_controls.py

@@ -10,13 +10,15 @@
 # Example code for running an building with smart panel controls.
 
 main_output_path = dwelling_args.pop("output_path", os.getcwd())
-dwelling_args.update({
-    "name": "ochre",
-    "time_res": dt.timedelta(minutes=2),  # time resolution of the simulation
-    "duration": dt.timedelta(days=10),  # duration of the simulation
-    "verbosity": 6,  # verbosity of time series files (0-9)
-    'seed': 1,
-})
+dwelling_args.update(
+    {
+        "name": "ochre",
+        "time_res": dt.timedelta(minutes=2),  # time resolution of the simulation
+        "duration": dt.timedelta(days=10),  # duration of the simulation
+        "verbosity": 6,  # verbosity of time series files (0-9)
+        "seed": 1,
+    }
+)
 
 
 def circuit_sharing_control(dwelling, tech1, tech2):
@@ -209,7 +211,7 @@ def my_print(*args):
 
     # case 1, circuit sharing with cooking range (primary) and WH (secondary)
     run_simulation(
-        "circuit_sharing", 
+        "circuit_sharing",
         tech1="Cooking Range",
         tech2="Water Heating",
     )

changelog.md

@@ -2,6 +2,9 @@
 
 ### OCHRE v0.9.3
 - Allow 120V (aka low power) heat pump water heaters
+- Applied ruff code formatting to entire codebase
+- Fixed ruff lint errors across codebase
+- Updated CI to run tests on all pull requests
 
 ### OCHRE v0.9.2
 - Restrict pint version to avoid colab issues [#196](https://github.com/NREL/OCHRE/issues/196)